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Gamified Crowdsourcing as a Novel Approach to Lung Ultrasound Data Set Labeling: Prospective Analysis

Gamified Crowdsourcing as a Novel Approach to Lung Ultrasound Data Set Labeling: Prospective Analysis

The remaining clips from the complete data set were not labeled by experts but instead were available to achieve a crowd-consensus label. Crowd users were given additional performance feedback on clips that had previously achieved a crowd-consensus label. Expert and crowd users were asked to classify B-lines on lung POCUS clips into one of three classes: (1) no B-lines, (2) one or more discrete B-lines, or (3) confluent B-lines (Figure 2).

Nicole M Duggan, Mike Jin, Maria Alejandra Duran Mendicuti, Stephen Hallisey, Denie Bernier, Lauren A Selame, Ameneh Asgari-Targhi, Chanel E Fischetti, Ruben Lucassen, Anthony E Samir, Erik Duhaime, Tina Kapur, Andrew J Goldsmith

J Med Internet Res 2024;26:e51397